Purpose: To validate the quantification of training load (session rating of perceived exertion [s-RPE]) in an Australian Olympic squad (women’s water polo), assessed with the use of a modified RPE scale collected via a newly developed online system (athlete management system). Methods: Sixteen elite women water polo players (age = 26  y, height = 1.78 [0.05] m, and body mass = 75.5 [7.1] kg) participated in the study. Thirty training sessions were monitored for a total of 303 individual sessions. Heart rate was recorded during training sessions using continuous heart-rate telemetry. Participants were asked to rate the intensity of the training sessions on the athlete management system RPE scale, using an online application within 30 min of completion of the sessions. Individual relationships between s-RPE and both Banister training impulse (TRIMP) and Edwards’ method were analyzed. Results: Individual correlations with s-RPE ranged between r = .51 and .79 (Banister TRIMP) and r = .54 and .83 (Edwards’ method). The percentages of moderate and large correlation were 81% and 19% between s-RPE method and Banister TRIMP, and 56% and 44% between s-RPE and Edwards’ method. Conclusions: The online athlete management system for assessing s-RPE was shown to be a valid indicator of internal training load and can be used in elite sport.
Miranda J. Menaspà, Paolo Menaspà, Sally A. Clark and Maurizio Fanchini
Paolo Menaspà, Chris R. Abbiss and David T. Martin
This investigation describes the sprint performances of the highest internationally ranked professional male road sprint cyclist during the 2008–2011 Grand Tours. Sprint stages were classified as won, lost, or dropped from the front bunch before the sprint. Thirty-one stages were video-analyzed for average speed of the last km, sprint duration, position in the bunch, and number of teammates at 60, 30, and 15 s remaining. Race distance, total elevation gain (TEG), and average speed of 45 stages were determined. Head-to-head performances against the 2nd–5th most successful professional sprint cyclists were also reviewed. In the 52 Grand Tour sprint stages the subject started, he won 30 (58%), lost 15 (29%), was dropped in 6 (12%), and had 1 crash. Position in the bunch was closer to the front and the number of team members was significantly higher in won than in lost at 60, 30, and 15 s remaining (P < .05). The sprint duration was not different between won and lost (11.3 ± 1.7 and 10.4 ± 3.2 s). TEG was significantly higher in dropped (1089 ± 465 m) than in won and lost (574 ± 394 and 601 ± 423 m, P < .05). The ability to finish the race with the front bunch was lower (77%) than that of other successful sprinters (89%). However, the subject was highly successful, winning over 60% of contested stages, while his competitors won less than 15%. This investigation explores methodology that can be used to describe important aspects of road sprint cycling and supports the concept that tactical aspects of sprinting can relate to performance outcomes.
Chris R. Abbiss, Paolo Menaspà, Vincent Villerius and David T. Martin
A number of laboratory-based performance tests have been designed to mimic the dynamic and stochastic nature of road cycling. However, the distribution of power output and thus physical demands of high-intensity surges performed to establish a breakaway during actual competitive road cycling are unclear. Review of data from professional road-cycling events has indicated that numerous short-duration (5–15 s), high-intensity (~9.5–14 W/kg) surges are typically observed in the 5–10 min before athletes’ establishing a breakaway (ie, riding away from a group of cyclists). After this initial high-intensity effort, power output declined but remained high (~450–500 W) for a further 30 s to 5 min, depending on race dynamics (ie, the response of the chase group). Due to the significant influence competitors have on pacing strategies, it is difficult for laboratory-based performance tests to precisely replicate this aspect of mass-start competitive road cycling. Further research examining the distribution of power output during competitive road racing is needed to refine laboratory-based simulated stochastic performance trials and better understand the factors important to the success of a breakaway.
Paolo Menaspà, Ermanno Rampinini, Lara Tonetti and Andrea Bosio
To describe the physical fitness of a top-level lower limb amputee (LLA) cyclist and paracycling time-trial (TT) race demands.
The 40-y-old male unilateral transfemoral amputee TT World Champion was tested in a laboratory for peak oxygen uptake (VO2peak), ventilatory threshold (VT2), power output (PO), and hemoglobin mass (Hb-mass). Moreover, several measures (eg, PO, heart rate [HR], cadence) were collected during 4 international TT competitions in the same season. The races’ intensity was evaluated as time spent below, at, or above VT2.
The cyclist (1.73 m, 55.0 kg) had a VO2peak of 3.372 L/min (61.3 mL · kg−1 · min−1). The laboratory peak PO was 315 W (5.7 W/kg). The maximal HR was 208 beats/min, and his Hb-mass was 744 g (13.5 g/kg). The TTs were meanly 18 ± 4.5 km in length, and the mean PO was 248 ± 8 W with a cadence of 92 ± 1 rpm. During the TTs, the cyclist spent 23% ± 9% of total time at VT2, 59% ± 10% below, and 18% ± 5% above this intensity.
The subject’s relative VO2peak is higher than previously published data on LLA, and surprisingly it is even higher than “good” ACSM normative data for nondisabled people. The intensity of the races was found to be similar to cycling TTs of the same duration in elite female cyclists. These results might be useful to develop specific training schedules and enhance performance of LLA cyclists.
Paul F.J. Merkes, Paolo Menaspà and Chris R. Abbiss
Purpose: To assess the influence of seated, standing, and forward-standing cycling sprint positions on aerodynamic drag (CdA) and the reproducibility of a field test of CdA calculated in these different positions. Methods: A total of 11 recreational male road cyclists rode 250 m in 2 directions at around 25, 32, and 40 km·h−1 and in each of the 3 positions, resulting in a total of 18 efforts per participant. Riding velocity, power output, wind direction and velocity, road gradient, temperature, relative humidity, and barometric pressure were measured and used to calculate CdA using regression analysis. Results: A main effect of position showed that the average CdA of the 2 d was lower for the forward-standing position (0.295 [0.059]) compared with both the seated (0.363 [0.071], P = .018) and standing positions (0.372 [0.077], P = .037). Seated and standing positions did not differ from each other. Although no significant difference was observed in CdA between the 2 test days, a poor between-days reliability was observed. Conclusion: A novel forward-standing cycling sprint position resulted in 23% and 26% reductions in CdA compared with a seated and standing position, respectively. This decrease in CdA could potentially result in an important increase in cycling sprint velocity of 3.9–4.9 km·h−1, although these results should be interpreted with caution because poor reliability of CdA was observed between days.
Paolo Menaspà, Marco Sias, Gene Bates and Antonio La Torre
Purpose: To describe the demand of recent World Cup (WC) races comparing top-10 (T10) and non-top-10 (N-T10) performances using power data. Methods: Race data were collected in 1-d World Cup races during the 2012–2015 road cycling seasons. Seven female cyclists completed 49 WC races, finishing 25 times in T10 and 24 times in N-T10. Peak power (1 s) and maximal mean power (MMP) for durations of 5, 10, 20, and 30 s and 1, 2, 5, 10, 20, 30, and 60 min expressed as power to weight ratio were analyzed in T10 and N-T10. The percentage of total race time spent at different power bands was compared between T10 and N-T10 using 0.75-W·kg−1 power bands, ranging from <0.75 to >7.50 W·kg−1. The number of efforts in which the power output remained above 7.50 W·kg−1 for at least 10 s was recorded. Results: MMPs were significantly higher in T10 than in N-T10, with a large effect size for durations between 10 s and 5 min. N-T10 spent more time in the 3.01- to 3.75-W·kg−1 power band when compared to T10 (P = .011); conversely, T10 spent more time in the 6.75- to 7.50- and >7.50-W·kg−1 power bands (P = .009 and .005, respectively) than N-T10. A significantly higher number of short and high-intensity efforts (≥10 s, >7.5 W·kg−1) was ridden by T10 than N-T10 (P = .002), specifically, 46 ± 20 and 30 ± 15 efforts for T10 and N-T10, respectively. Conclusions: The ability to ride at high intensity was determinant for successful road-cycling performances in WC races.
Paul F.J. Merkes, Paolo Menaspà and Chris R. Abbiss
Purpose: To determine the validity of the Velocomp PowerPod power meter in comparison with the Verve Cycling InfoCrank power meter. Methods: This research involved 2 separate studies. In study 1, 12 recreational male road cyclists completed 7 maximal cycling efforts of a known duration (2 times 5 s and 15, 30, 60, 240, and 600 s). In study 2, 4 elite male road cyclists completed 13 outdoor cycling sessions. In both studies, power output of cyclists was continuously measured using both the PowerPod and InfoCrank power meters. Maximal mean power output was calculated for durations of 1, 5, 15, 30, 60, 240, and 600 seconds plus the average power output in study 2. Results: Power output determined by the PowerPod was almost perfectly correlated with the InfoCrank (r > .996; P < .001) in both studies. Using a rolling resistance previously reported, power output was similar between power meters in study 1 (P = .989), but not in study 2 (P = .045). Rolling resistance estimated by the PowerPod was higher than what has been previously reported; this might have occurred because of errors in the subjective device setup. This overestimation of rolling resistance increased the power output readings. Conclusion: Accuracy of rolling resistance seems to be very important in determining power output using the PowerPod. When using a rolling resistance based on previous literature, the PowerPod showed high validity when compared with the InfoCrank in a controlled field test (study 1) but less so in a dynamic environment (study 2).
Paolo Menaspà, Franco M. Impellizzeri, Eric C. Haakonssen, David T. Martin and Chris R. Abbiss
To determine the consistency of commercially available devices used for measuring elevation gain in outdoor activities and sports.
Two separate observational validation studies were conducted. Garmin (Forerunner 310XT, Edge 500, Edge 750, and Edge 800; with and without elevation correction) and SRM (Power Control 7) devices were used to measure total elevation gain (TEG) over a 15.7-km mountain climb performed on 6 separate occasions (6 devices; study 1) and during a 138-km cycling event (164 devices; study 2).
TEG was significantly different between the Garmin and SRM devices (P < .05). The between-devices variability in TEG was lower when measured with the SRM than with the Garmin devices (study 1: 0.2% and 1.5%, respectively). The use of the Garmin elevation-correction option resulted in a 5–10% increase in the TEG.
While measurements of TEG were relatively consistent within each brand, the measurements differed between the SRM and Garmin devices by as much as 3%. Caution should be taken when comparing elevation-gain data recorded with different settings or with devices of different brands.
Jeremiah J. Peiffer, Chris R. Abbiss, Eric C. Haakonssen and Paolo Menaspà
Purpose: To examine the power-output distribution and sprint characteristics of professional female road cyclists. Methods: A total of 31 race files, representing top 5 finishes, were collected from 7 professional female cyclists. Files were analyzed for sprint characteristics, including mean and peak power output, velocity, and duration. The final 20 min before the sprint was analyzed to determine the mean maximal power output (MMP) consistent with durations of 5, 15, 30, 60, 240, and 600 s. Throughout the race, the number of efforts for each duration exceeding 80% of its corresponding final 20-min MMP (MMP80) was determined. The number of 15-s efforts exceeding 80% of the mean final sprint power output (MSP80) was determined. Results: Sprint finishes lasted 21.8 (6.7) s with mean and peak power outputs of 679 (101) and 886 (91) W, respectively. Throughout the race, additional 5-, 15-, and 30-s efforts above MMP80 were completed in the 5th compared with the 1st–4th quintiles of the race. The 60-s efforts were greater during the 5th quintile compared with the 1st, 2nd, and 4th quintiles, and during the 3rd compared with the 4th quintile. More 240-s efforts were recorded during the 5th compared with the 1st and 4th quintiles. About 82% of the 15-s efforts above MSP80 were completed in the 2nd, 3rd, and 5th quintiles of the race. Conclusions: These data demonstrate the variable nature of women’s professional cycling and the physical demands necessary for success, thus providing information that could enhance in-race decision making and the development of race-specific training programs.
Jason R. Boynton, Fabian Danner, Paolo Menaspà, Jeremiah J. Peiffer and Chris R. Abbiss
Purpose: To examine the effect of environmental temperature (T A) on performance and physiological responses (eg, body temperature, cardiopulmonary measures) during a high-intensity aerobic interval session. It was hypothesized that power output would be highest in the 13°C condition and lower in the 5°C, 22°C, and 35°C conditions. Methods: Eleven well-trained cyclists randomly completed 4 interval sessions at 5°C, 13°C, 22°C, and 35°C (55% [13%] relative humidity), each involving five 4-min intervals interspersed with 5 min of recovery. During the intervals, power output, core temperature (T C), skin temperature, VO2, and heart rate were recorded. Results: Mean session power output for 13°C (366  W) was not higher than 5°C (363  W; P = 1.00, effect size = 0.085), 22°C (364  W; P = 1.00, effect size = 0.061), or 35°C (352  W; P = .129, effect size = 0.441). The 5th interval of the 35°C condition had a lower power output compared with all other T A. T C was higher in 22°C compared with both 5°C and 13°C (P = .001). VO2 was not significantly different across T A (P = .187). Heart rate was higher in the 4th and 5th intervals of 35°C compared with 5°C and 13°C. Conclusions: This study demonstrates that while mean power outputs for intervals are similar across T A, hot T A (≥35°C) reduces interval power output later in a training session. Well-trained cyclists performing maximal high-intensity aerobic intervals can achieve near-optimal power output over a broader range of T A than previous literature would indicate.